A Survey of Mobile Cloud Computing Application Models

By Atta ur Rehman Khan, Mazliza Othman, S. Madani, Samee Ullah Khan. 2014

737 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, ML Systems & Hardware

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In Computer Networks and Communications

In Electrical and Electronic Engineering

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Citations in the corpus

Why Should We Add Early Exits to Neural Networks? (2020, background): “In fact, the general topic of the design of multi-tier FC platforms is receiving large attention in these last years, mainly due to the emerging areas of the Mobile Cloud, Per-vasive Computing and Edge Computing [ 54, 46 ] .”
A Distributed Truthful Auction Mechanism for Task Allocation in Mobile Cloud Computing (2018, background): “To alleviate resource scarcity of mobile devices, one effective way is to offload their complex or resourcedemanded tasks to remote cloud [5], [6], [7], [8] through pay as you go.”
Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds (2017, methodology): “1The program profiler monitors the program parameters, for instance, execution time, acquired memory, thread CPU time, number of instructions, and method calls [2].”
How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions (2017, background): “There are recent surveys on cloud computing [18], [19] and MCC [8], [20]–[22].”
Edge Computing with Artificial Intelligence: A Machine Learning Perspective (2022, background): “Equipped with a large number of remotely located servers, cloud computing can intelligently provide users with computing, storage, and network services in real time according to user needs in terms of resource type, quantity, and so on [1].”
EcoMobiFog–Design and Dynamic Optimization of a 5G Mobile-Fog-Cloud Multi-Tier Ecosystem for the Real-Time Distributed Execution of Stream Applications (2019, background): “, distant) resource-rich Cloud data centers for their execution [2].”
Data Security and Privacy-Preserving in Edge Computing Paradigm: Survey and Open Issues (2018, background): “Previous work such as micro data center, [19], [20], mobile cloud computing [13], [14], fog computing [15], [16], cloudlet [21], and cloud-sea computing [22] have been introduced to reduce the storage and computation load in cloud computing.”
Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices (2016, background): “the advent of a mature mobile application market [2].”
Price-Based Distributed Offloading for Mobile-Edge Computing With Computation Capacity Constraints (2017, background): “However, the IoT devices are usually with small physical sizes and limited batteries, thus always suffer from intensive computation and high resource-consumption for real-time information processing [1]–[3].”
A Survey of Mobile Device Virtualization (2016, background): “…mobile devices have transitioned from handheld sets, which enable simple voice and message services, to smartphones, which host multiple applications with high performance requirements, such as video processing, object recognition, and interactive games [Khan et al. 2014; Ahmed et al. 2015].”
Joint Offloading and Trajectory Design for UAV-Enabled Mobile Edge Computing Systems (2019, background): “However, the limited computation resources and battery budget make it difficult for mobile devices to provide satisfactory quality of experience (QoE) [2].”
Internet of Things for Smart Healthcare: Technologies, Challenges, and Opportunities (2017, background): “The aforementioned surveys in [116] and [117] present comprehensive overviews of the works in this field, and demonstrate that energy efficiency and higher processing capabilities can be readily achieved when utilized computational offloading to the cloud.”
A Survey on Mobile Edge Computing: The Communication Perspective (2017, background): “Server hardware Small-scale data centers Large-scale data centers (each contains with moderate resources [5], [21] a large number of highly-capable servers) [22], [23]”
Security in cloud computing: Opportunities and challenges (2015, background): “The aforementioned limitations served as motivation for a new computing paradigm called MCC that enhances the abilities of mobile devices by moving the storage and compute intensive tasks of mobile to the cloud [56,82].”